14 - 2/23/12 Initial setup 1. Open Wolfram CDF Player and...

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Unformatted text preview: 2/23/12 Initial setup 1. Open Wolfram CDF Player and RandomWalkCircles 5 simulation. Click “Enable Dynamics” button. 2. Adjust the stimulation window by expanding the inner square to fill the screen as shown here. 3. Open your Google account and use the link emailed to you to open “BSCI207Diffusion_DataSpr12” spreadsheet. 4. Play with the simulation according to the instructions on the handout. Diffusion in Cells Diffusion works fine across membranes, organelles, and most cells In general, no need to evolve special mechanisms for facilitating the movement of most molecules via diffusion over short distances. (Exception: the challenge of membrane permeability) Multicellular eukaryotes: The limits of diffusion Learning objectives: 1) To visualize how the random movement of molecules can result in their net movement down a concentration gradient; 2) To gain a quantitative perspective of how the diffusion works as a physical process; and 3) To analyze how the limits of diffusion have affected the evolution and functioning of large multicellular organisms in eukaryotic lineages. In-class activities: computer simulations for understanding the fundamental principles governing diffusion as a physical process Group homework: several problems for illustrating the role of diffusion in biological systems. Homework assignment will be posted on the class website. Due next Friday. Transport systems in animals ventilatory, circulatory, digestive, and excretory systems F Fig. 44.11 arditobook.pbworks.com/The-Circulatory-System Ventilation •  Convection of medium (air) •  Diffusion of O2 and CO2 across alveolar membranes Circulation •  Convection of medium (blood) •  Diffusion of gases, food molecules, waste molecules across capillary membranes 1 2/23/12 Simulation #1 - Tuning everyone’s computer Noise – 0.012 Particles -100 Time - 20 sec 10-15 particles outside or on circle 4 -> no reset Otherwise – reset noise and rerun simulation Simulation #2 - to obtain a qualitative sense for how diffusion works Settings - Noise at 0.03 Particles at 100 Run the simulation and watch what happens. Simulations #3-#5 – to obtain a quantitative perspective of the relationship between concentration gradient (i.e., a concentration difference over a distance) and diffusion rate (Fick’s First Law) #3 Noise at reset level from simulation #1 Particle number – 50 Run time – 20 s Data collection – count the number of particles on or outside circle 4 Enter the data in the table Recenter all particles, repeat twice, and calculate mean particle number #4 Same, but set particle number – 100 #5 Same, but particle number – 150 Fill out the row for your group data on the Google docs spreadsheet called “BSCI207Diffusion_DataSpr12” which is accessed via your Google account. Simulation #6 – to determine the quantitative relationship between time and distance traveled for individual molecules (Time-to-Diffuse equation, also called the Einstein-Smoluchowski relation) Settings – Noise at the reset level from simulation #1 Particles at 5 Run the simulation for 20 s intervals (do not recenter!) Measure the distance of each particle from the 0 circle to the closest circle, which corresponds to the distance traveled 2 ...
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This note was uploaded on 04/05/2012 for the course BSCI 207 taught by Professor Higgins during the Spring '08 term at Maryland.

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